{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 代码实现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入必要的库\n",
    "import numpy as np\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import matplotlib.pyplot as plt # 用于数据可视化\n",
    "from torch.utils.data import DataLoader, TensorDataset # 用于构造数据加载器\n",
    "from sklearn.model_selection import train_test_split # 用于划分数据集"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据生成"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设置随机种子\n",
    "np.random.seed(32)\n",
    "\n",
    "# 生成满足 y = x^2 + 1 的数据\n",
    "num_samples = 100 # 100个样本点\n",
    "X = np.random.uniform(-5, 5, (num_samples, 1)) # 均匀分布\n",
    "Y = X ** 2 + 1 + 5 * np.random.normal(0, 1, (num_samples, 1)) # 正态分布噪声\n",
    "\n",
    "# 将 NumPy 变量转化为浮点型 PyTorch 变量\n",
    "X = torch.from_numpy(X).float()\n",
    "Y = torch.from_numpy(Y).float()\n",
    "\n",
    "# 绘制数据散点图\n",
    "plt.scatter(X, Y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据划分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将数据拆分为训练集和测试集\n",
    "train_X, test_X, train_Y, test_Y = train_test_split(X, Y, test_size=0.3, random_state=0)\n",
    "\n",
    "# 将数据封装成数据加载器\n",
    "train_dataloader = DataLoader(TensorDataset(train_X, train_Y), batch_size=32, shuffle=True)\n",
    "test_dataloader = DataLoader(TensorDataset(test_X, test_Y), batch_size=32, shuffle=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 模型定义"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 定义线性回归模型（欠拟合）\n",
    "class LinearRegression(nn.Module):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.linear = nn.Linear(1, 1)\n",
    "\n",
    "    def forward(self, x):\n",
    "        return self.linear(x)\n",
    "\n",
    "# 定义多层感知机（正常）\n",
    "class MLP(nn.Module):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.hidden = nn.Linear(1, 8)\n",
    "        self.output = nn.Linear(8, 1)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = torch.relu(self.hidden(x))\n",
    "        return self.output(x)\n",
    "\n",
    "# 定义更复杂的多层感知机（过拟合）\n",
    "class MLPOverfitting(nn.Module):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.hidden1 = nn.Linear(1, 256)\n",
    "        self.hidden2 = nn.Linear(256, 256)\n",
    "        self.output = nn.Linear(256, 1)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = torch.relu(self.hidden1(x))\n",
    "        x = torch.relu(self.hidden2(x))\n",
    "        return self.output(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 辅助函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_errors(models, num_epochs, train_dataloader, test_dataloader):\n",
    "    # 定义损失函数\n",
    "    loss_fn = nn.MSELoss()\n",
    "\n",
    "    # 定义训练和测试误差数组\n",
    "    train_losses = []\n",
    "    test_losses = []\n",
    "\n",
    "    # 遍历每类模型\n",
    "    for model in models:\n",
    "        # 定义优化器\n",
    "        optimizer = torch.optim.SGD(model.parameters(), lr=0.005)\n",
    "\n",
    "        # 每类模型的训练和测试误差\n",
    "        train_losses_per_model = []\n",
    "        test_losses_per_model = []\n",
    "        \n",
    "        # 迭代训练\n",
    "        for epoch in range(num_epochs):\n",
    "            # 在训练数据上迭代\n",
    "            model.train()\n",
    "            train_loss = 0\n",
    "            # 遍历训练集\n",
    "            for inputs, targets in train_dataloader:\n",
    "                # 预测、损失函数、反向传播\n",
    "                optimizer.zero_grad()\n",
    "                outputs = model(inputs)\n",
    "                loss = loss_fn(outputs, targets)\n",
    "                loss.backward()\n",
    "                optimizer.step()\n",
    "                # 记录loss\n",
    "                train_loss += loss.item()\n",
    "            \n",
    "            # 计算loss并记录\n",
    "            train_loss /= len(train_dataloader)\n",
    "            train_losses_per_model.append(train_loss)\n",
    "\n",
    "            # 在测试数据上评估，测试模型不计算梯度\n",
    "            model.eval()\n",
    "            test_loss = 0\n",
    "            with torch.no_grad():\n",
    "                # 遍历测试集\n",
    "                for inputs, targets in test_dataloader:\n",
    "                    # 预测、损失函数\n",
    "                    outputs = model(inputs)\n",
    "                    loss = loss_fn(outputs, targets)\n",
    "                    # 记录loss\n",
    "                    test_loss += loss.item()\n",
    "            \n",
    "                # 计算loss并记录\n",
    "                test_loss /= len(test_dataloader)\n",
    "                test_losses_per_model.append(test_loss)\n",
    "\n",
    "        # 记录当前模型每轮的训练测试误差\n",
    "        train_losses.append(train_losses_per_model)\n",
    "        test_losses.append(test_losses_per_model)\n",
    "\n",
    "    return train_losses, test_losses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# 获取训练和测试误差曲线数据\n",
    "num_epochs = 200\n",
    "models = [LinearRegression(), MLP(), MLPOverfitting()]\n",
    "train_losses, test_losses = plot_errors(models, num_epochs, train_dataloader, test_dataloader)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制训练和测试误差曲线\n",
    "for i, model in enumerate(models):\n",
    "    plt.figure(figsize=(8, 4))\n",
    "    plt.plot(range(num_epochs), train_losses[i], label=f\"Train {model.__class__.__name__}\")\n",
    "    plt.plot(range(num_epochs), test_losses[i], label=f\"Test {model.__class__.__name__}\")\n",
    "    plt.legend()\n",
    "    plt.ylim((0, 200))\n",
    "    plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
